Weak or manual product recommendations
Let AI run recommendations on autopilot, or take the wheel yourself
Maestra Platform combines a marketing personalization platform with a dedicated forward-deployed marketer, giving ecommerce brands AI-driven picks and the business rules to override them whenever merchandising needs to step in.
Brands running on Maestra
The problem
Merchandising by hand doesn't scale past a handful of SKUs
Someone on the team is still hand-selecting which products show up in each recommendation slot, one placement at a time. It works for a small catalog, but every new SKU adds more manual work, and most of the catalog never gets a proper recommendation at all.
What we hear from brands
a leather handbag brand's small ecommerce team manually manages merchandising and A/B tests, limiting scale
an automotive parts retailer describes manual, time-consuming setup of upsells and bundles as SKU count expands
a men's grooming brand cites underperforming product pages and lean team bandwidth for testing and optimization
The new way
One set of recommendations, synced everywhere a customer shops
The same product logic that powers your website also fills recommendation blocks in email, SMS, messengers, and even in-store POS. A customer who browses a product on-site sees a relevant follow-up in their next email, not a generic bestseller list pulled from a different system.
Outcomes brands report
Customer proof
Unidragon found 7.4% of revenue hiding in customers who never left one category
Most Unidragon customers stuck to a single puzzle category, unaware of the brand's full collection, and limited cross-category discovery kept buyers from exploring other designs. A post-purchase email flow recommending new categories based on past purchases became one of the brand's top revenue-generating flows.
“The results exceeded our expectations, it became one of our top revenue-generating flows. It’s a great example of how smart automation can deliver strong results with minimal effort.”
Read the full case study7.4%
of total revenue generated through a personalized cross-sell flow
How it works
A migration built to protect revenue, not just data
Access and a plan, nothing more
You provide access to your current systems and approve the migration roadmap your forward-deployed marketer puts together.
Parallel systems, zero downtime
Your old stack keeps running the entire time, so there is no gap in sending, tracking, or customer experience.
Warm-up handled before you launch
Deliverability warm-up runs as part of the transition, so your first campaigns on Maestra land in the inbox, not the spam folder.
The platform
The platform behind every touchpoint
Maestra combines a real-time CDP, on-site personalization, and every messaging channel into a single system, all running on a data model built specifically for commerce. It scales to 2M RPM and responds in under 300 milliseconds, so it works at the speed customers actually browse.
Your forward-deployed marketer
Support that scales down the account load, not up
Instead of pooling customers across a large support team, Maestra keeps each forward-deployed marketer under 15 accounts. Fewer accounts means more meetings, faster replies, and more of the work actually getting done for you.
Fewer than 15 accounts per marketer, versus 60+
4 meetings a month versus 1
Done-for-you flows and A/B tests
Replace your stack
Three to five tools doing the same job, badly
Most brands auditing their stack find three to five tools with overlapping functions and no shared data. Maestra is built to absorb that overlap into native modules for email, SMS, loyalty, on-site personalization, and recommendations.
Replaces
Klaviyo
Attentive
Yotpo
Rebuy
Segment
400+ use cases, one platform to see them in
There is a good chance your use case is already solved. Book a demo and we will show you where.